The main goal of this paper is to better understand the behavior of credit spreads in the past and the potential risk of unexpected future credit spread changes. One important consideration to note regarding credit spreads is the fact that bond spreads contain a liquidity premium, which...

Using Gretl, I apply ARMA, Vector ARMA, VAR, state-space model with a Kalman filter, transfer-function and intervention models, unit root tests, cointegration test, volatility models (ARCH, GARCH, ARCH-M, GARCH-M, Taylor-Schwert GARCH, GJR, TARCH, NARCH, APARCH, EGARCH) to analyze quarterly time...

In this paper we show how the assumption that higher moments do not depend on the regressors can be exploited in a GMM framework, and we provide very simple estimators that are equivalent to GMM estimators. These simple estimators can be calculated by linear regressions which have been augmented...

Beginning with the recent reorganisation of the principal Italian public research bodies, which has led to the founding of larger labs, this paper evaluates the presence of statistically significant relationships between the dimensions of the research bodies and the performance of the same. The...

This article gives the asymptotic properties for nonparametric kernel based density and regression estimators when one of the variables, respectively regressors, had to be pre-estimated. Those variables are known as constructed variables or generatedregressors, and their impact on the -nal...

The authors propose a nonparametric test for white noise hypothesis in a regression model. The test is based on a regressogram estimate, which bin width is selected using a penalty method similar to the AIC, BIC, and C'ps MAllows criteria.

It is now widely believed that Foreign Direct Investment (FDI) affects positively the productivity of individual enterprises in the host economy and this is a main argument in favour of FDI. Although China is the largest recipient of FDI after the USA, there has been little empirical research as...

This paper shows how Bayesian inference for switching regression models and their generalisations can be achieved by the specification of loss functions which overcome the label switching problem common to all mixture models. We also derive an extension to models where the number of components...